A novel method for browser fingerprinting using ad blocker signals has been introduced, expanding on the theoretical discussions by providing a practical implementation as of April 2021. Ad blockers, used by approximately 26% of Americans, leave identifiable traces that websites can harness to improve visitor identification by examining discrepancies in the filters used by specific ad blockers. This method generates a unique user identifier by combining these signals with other browser attributes. The article delves into the mechanics of ad blockers, explaining that they operate by hiding elements via CSS or blocking resources at the network level, with variations in implementation across different browsers like Chrome, Firefox, and Safari. The process of using ad blocker signals involves detecting blocked CSS selectors and unique filters, offering a way to create fingerprints that remain effective even in incognito modes on certain platforms. This technique is a part of the broader Fingerprint library, which aims to enhance online security by providing a robust identification method that can be particularly useful for anti-fraud applications.